PhD student 10: Computational models for thermomagnetic materials

Objectives

Establish a mesoscopic model for thermal hysteresis. Optimization of thermomagnetic materials.

• Mesoscopic multi-physics simulator of thermomagnetic properties. Using a software library for solving partial differential equations, a micromagnetic finite element solver will be augmented with magneto-structural coupling and a phase field model.
• Standard problems for thermomagnetic simulations. Like the micromagnetic standard problems, a suite of problems for thermomagnetic simulations will be defined and used to test and verify the newly developed software.
• Machine learning model of thermal hysteresis. Combining data from thin film combinatorial studies and thermomagnetic simulations, a machine learning model will be built to predict thermal hysteresis based on chemical composition and the material microstructure.
• Guidelines for optimization of thermomagnetic materials. Ideal composition and microstructure combinations through genetic optimization.

Universität für Weiterbildung Krem

PhD enrollment at TU Wien

Radboud University

Institut Néel - Centre National de la Recherche Scientifique

Magneto B.V.